NormData: Derivation of Regression-Based Normative Data

Normative data are often used to estimate the relative position of a raw test score in the population. This package allows for deriving regression-based normative data. It includes functions that enable the fitting of regression models for the mean and residual (or variance) structures, test the model assumptions, derive the normative data in the form of normative tables or automatic scoring sheets, and estimate confidence intervals for the norms. This package accompanies the book Van der Elst, W. (2024). Regression-based normative data for psychological assessment. A hands-on approach using R. Springer Nature.

Version: 1.1
Depends: R (≥ 3.5.0)
Imports: car, doBy, MASS, lmtest, dplyr, sandwich, openxlsx, methods
Published: 2024-04-12
Author: Wim Van der Elst ORCID iD [aut, cre]
Maintainer: Wim Van der Elst <Wim.vanderelst at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: NormData results

Documentation:

Reference manual: NormData.pdf

Downloads:

Package source: NormData_1.1.tar.gz
Windows binaries: r-prerel: NormData_1.1.zip, r-release: NormData_1.1.zip, r-oldrel: NormData_1.1.zip
macOS binaries: r-prerel (arm64): NormData_1.1.tgz, r-release (arm64): NormData_1.1.tgz, r-oldrel (arm64): NormData_1.1.tgz, r-prerel (x86_64): NormData_1.1.tgz, r-release (x86_64): NormData_1.1.tgz
Old sources: NormData archive

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